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CSL 859: Advanced Computer Graphics. Dept of Computer Sc. & Engg. IIT Delhi. Image-Based Rendering. So far: Geometry -> images Object space model, even volumetric Image-based rendering : Image -> Another image Zoom, Pan etc. Just image processing?. Images with depth. Quicktime VR:
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CSL 859: Advanced Computer Graphics Dept of Computer Sc. & Engg. IIT Delhi
Image-Based Rendering • So far: • Geometry -> images • Object space model, even volumetric • Image-based rendering: • Image -> Another image • Zoom, Pan etc. • Just image processing?
Images with depth • Quicktime VR: • 2D panoramic photograph • Spin around, zoom in and out • Can add objects closer to viewer • Tour into the picture • Assign depth to parts of the image • One might add objects hidden behind some object in the image • Layered depth images
Image Based Rendering • Store image from every conceivable view • Rendering would reduce to database query • Generality demand infinite sized database • Could store enough images • Given a desired viewpoint (viewmatrix) • Choose an image from a saved view near the desired view • Warp the image • Or, interpolate from nearby known viewpoints
Warp x1 to x2+ Correspondence
General 3D Warp [Courtesy L Mcmillan]
Occlusion Determination • Project the desired center-of-projection onto the reference image
Occlusion Determination • Draw towards the projected point • Guarantees painter’s ordering • Independent of the scene's contents • Generalizes to non-planar viewing surfaces
Radiances in a Scene • Account for all rays • Origin • 3 dimensions • Direction • 2 dimensions • Space of rays is 5 dimensional
Panorama All rays from a single point
Plenoptic Function All rays from all points p =P(Θ, Φ, x, y, z, λ, t) Courtesy L. Mcmillan
Radiances in a Scene II • Account for all rays • Origin • 3 dimensions • Direction • 2 dimensions • Space of rays is 5 dimensional • Radiance is constant along ray • 4 dimensional space • Subject to occlusion
Capturing Radiances • Capture images from many places • Camera positioning • Parameterize the 4D space • Camera position and 2D image? • Sample the 4D space • Coverage and sampling uniformity • Aliasing • Too much data
Representing Scene Radiance • Like texture map • Except ray origin is not fixed • Source and destination of ray varies • 2 coordinates (u,v) for ray origin • 2 coordinates (s,t) for ray destination v t u s [Light-field: Hanrahan & Levoy]
Ray Target Ray Source With four slabs the (r,θ) space is well covered (for an outside looking in case) Sampling Coverage θ θ r r
Stanford Multi-camera Array • 640 × 480 pixels ×30 fps × 128 cameras • Synchronized timing • Continuous streaming • Flexible arrangement
Rendering of Light Fields • For each pixel (x, y) • Compute ray • Map to (u,v,s,t) • Look up “4D” texture • Store as many 2D textures • Quadri-linear interpolation
Good and Bad • Advantages: • Simpler computation vs. traditional CG • Cost independent of scene complexity • Cost independent of material properties and other optical effects • Disadvantages: • Static geometry • Fixed lighting • High storage cost